In wireless communication systems, a variation of the signal strength of a communication channel may occur e.g. due to environmental variations caused by a movement of a wireless terminal (due to multipath propagation variations, or to shadowing from obstacles); such channel is also being referred to as a fading channel. The channel quality of a fading channel might vary over time, frequency and space. If the channel quality is accurately estimated at a receiver's side, e.g. one of the terminals, it can be exploited by a transmitter, e.g. a base station of the mobile communications network to optimize the data transmission. In particular, in frequency division duplexing (FDD) systems including systems based on orthogonal frequency-division multiplexing OFDM, the terminals might estimate the channel quality to be fed back to the transmitter within a reasonably short feedback time. If the transmitter has the knowledge of downlink channel quality, the average throughput (and thus spectral efficiency) at the receiver side can be maximized while maintaining certain Quality of Service (QoS) parameters, e.g. a guaranteed bit-error rate.
A general problem for channel quality estimation is to estimate a block error rate (BLER) for a data packet transmitted over a communication channel using a plurality of sub channels, especially in OFDM systems, wherein a communication channel is divided into a multiple (narrow-band) sub-carriers, which allows orthogonal modulated streams of data to be transmitted in parallel on the sub carriers, assuming that the current propagation channel conditions in a frequency selective fading channel having different signal-to-interference-noise-ratios (SINR) per sub-carrier.
There are well known CQI estimation methods discussed in literature, e.g. a method called Exponential Effective SNR Mapping (EESM) being described in a document titled “System-level evaluation of OFDM—further considerations”, published by 3GPP under the document number TSG-RAN WG1, R1-031303, Nov. 17-21, 2003 and a method called Mutual Information Effective SNR Mapping (MIESM), e.g. being described in the document titled “Effective-SNR mapping for modeling frame error rates in multiple-state channels”, published by 3GPP under the document number C30-20030429-010, WG RAN1, 2003. Both methods use reference signals, i.e. utilize the estimated channel and noise variance for the computation of a channel quality indicator CQI.
If linear receivers (e.g., zero-forcing or minimum mean square error) are employed, the estimated effective channel and noise variance e.g. based on (cell-specific) reference signals might be used for CQI determination by post-processing SINRs and calculating an effective SNR value based on the post-processed SINRs.
However, CQI estimation based on common (cell-specific) reference signals might not be accurate enough if it does not precisely account for channel estimation errors. Furthermore, if maximum likelihood detectors are used rather than the linear equalizers, then the CQI can't be estimated employing EESM or MIESM methods, as such detectors are not able to deliver SINRs.